If I want to compare two regression models using cross-validation, should I use the same partitions of training and test data for both of the models?
For example, suppose I fit a linear model with one predictor and then the same model but with one added predictor. Is it important I use the same split of the data into test and training samples? Or does it not matter? Or is using different splits actually preferred?